Expressing Emotion in Text-based Communication

被引:0
|
作者
Hancock, Jeffrey T. [1 ]
Landrigan, Christopher [1 ]
Silver, Courtney [1 ]
机构
[1] Cornell Univ, Dept Commun, Ithaca, NY 14853 USA
关键词
computer-mediated communication; emotion; affect;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Our ability to express and accurately assess emotional states is central to human life. The present study examines how people express and detect emotions during text-based communication, an environment that eliminates the nonverbal cues typically associated with emotion. The results from 40 dyadic interactions suggest that users relied on four strategies to express happiness versus sadness, including disagreement, negative affect terms, punctuation, and verbosity. Contrary to conventional wisdom, communication partners readily distinguished between positive and negative valence emotional communicators in this text-based context. The results are discussed with respect to the Social Information Processing model of strategic relational adaptation in mediated communication.
引用
收藏
页码:929 / 932
页数:4
相关论文
共 50 条
  • [1] Effectiveness of Extrinsic Emotion Regulation Strategies in Text-Based Online Communication
    Nozaki, Yuki
    Mikolajczak, Moira
    EMOTION, 2022, : 1714 - 1725
  • [2] Text-Based Emotion Recognition Approach
    Razek, Mohammed Abdel
    Frasson, Claude
    INTELLIGENT TUTORING SYSTEMS, ITS 2016, 2016, 9684 : 500 - 501
  • [3] Uncovering the Limits of Text-based Emotion Detection
    Alvarez-Gonzalez, Nurudin
    Kaltenbrunner, Andreas
    Gomez, Vicenc
    FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, EMNLP 2021, 2021, : 2560 - 2583
  • [4] Text-based emotion classification using emotion cause extraction
    Li, Weiyuan
    Xu, Hua
    EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (04) : 1742 - 1749
  • [5] Challenges and Opportunities of Text-Based Emotion Detection: A Survey
    Al Maruf, Abdullah
    Khanam, Fahima
    Haque, Md. Mahmudul
    Jiyad, Zakaria Masud
    Mridha, M. F.
    Aung, Zeyar
    IEEE ACCESS, 2024, 12 : 18416 - 18450
  • [6] Using YouTube comments for text-based emotion recognition
    Yasmina, Douiji
    Hajar, Mousannif
    Hassan, Al Moatassime
    7TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT 2016) / THE 6TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT-2016) / AFFILIATED WORKSHOPS, 2016, 83 : 292 - 299
  • [7] Text-Based Fine-Grained Emotion Prediction
    Singh, Gargi
    Brahma, Dhanajit
    Rai, Piyush
    Modi, Ashutosh
    IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2024, 15 (02) : 405 - 416
  • [8] Text-based emotion detection: Advances, challenges, and opportunities
    Acheampong, Francisca Adoma
    Chen Wenyu
    Nunoo-Mensah, Henry
    ENGINEERING REPORTS, 2020, 2 (07)
  • [9] Influence diffusion model in text-based communication
    Matsumura, Naohiro
    Ohsawa, Yukio
    Ishizuka, Mitsuru
    Transactions of the Japanese Society for Artificial Intelligence, 2002, 17 (03) : 259 - 267
  • [10] Multimodal text-emoji fusion using deep neural networks for text-based emotion detection in online communication
    Kusal, Sheetal
    Patil, Shruti
    Kotecha, Ketan
    JOURNAL OF BIG DATA, 2025, 12 (01)